Variable.h

// Copyright 2024, UChicago Argonne, LLC
// All Rights Reserved
// Software Name: NEML2 -- the New Engineering material Model Library, version 2
// By: Argonne National Laboratory
// OPEN SOURCE LICENSE (MIT)
//
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// furnished to do so, subject to the following conditions:
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// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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// THE SOFTWARE.
 
#pragma once
 
#include "neml2/tensors/LabeledAxisAccessor.h"
#include "neml2/tensors/tensors.h"
#include "neml2/tensors/LabeledVector.h"
#include "neml2/tensors/LabeledMatrix.h"
#include "neml2/tensors/LabeledTensor3D.h"
 
namespace neml2
{
using VariableName = LabeledAxisAccessor;
 
// Forward declarations
class Derivative;
class Model;
 
class VariableBase
{
public:
  VariableBase(const VariableName & name_in, const Model * owner);
 
  virtual ~VariableBase() = default;
 
  virtual void cache(TensorShapeRef batch_shape);
 
  virtual void setup_views(const LabeledVector * value,
                           const LabeledMatrix * deriv = nullptr,
                           const LabeledTensor3D * secderiv = nullptr);
 
  virtual void setup_views(const VariableBase * other);
 
  virtual void requires_grad_(bool req = true) = 0;
 
  Derivative d(const VariableBase & x);
 
  Derivative d(const VariableBase & x1, const VariableBase & x2);
 
  const Tensor & raw_value() const { return _raw_value; }
 
  virtual const Tensor tensor() const = 0;
 
  const VariableName & name() const { return _name; }
 
  const Model & owner() const { return *_owner; }
 
  const VariableBase * src() const { return _src; }
 
  TensorShapeRef batch_sizes() const { return _batch_sizes; }
 
  virtual TensorShapeRef base_sizes() const = 0;
 
  Size batch_dim() const { return _batch_sizes.size(); }
 
  Size base_dim() const { return base_sizes().size(); }
 
  Size base_storage() const { return utils::storage_size(base_sizes()); }
 
  virtual TensorShapeRef sizes() const = 0;
 
  virtual TensorType type() const = 0;
 
  bool is_state() const { return _is_state; }
  bool is_old_state() const { return _is_old_state; }
  bool is_force() const { return _is_force; }
  bool is_old_force() const { return _is_old_force; }
  bool is_residual() const { return _is_residual; }
  bool is_parameter() const { return _is_parameter; }
  bool is_other() const { return _is_other; }
  bool is_solve_dependent() const { return _is_solve_dependent; }
 
  // Note that the check depends on whether we are currently solving nonlinear system
  bool is_dependent() const;
 
protected:
  const VariableName _name;
 
  const Model * _owner;
 
  TensorShape _batch_sizes;
 
  Tensor _raw_value;
 
  std::map<VariableName, Tensor> _dvalue_d;
 
  std::map<VariableName, std::map<VariableName, Tensor>> _d2value_d;
 
  const VariableBase * _src;
 
  const bool _is_state;
  const bool _is_old_state;
  const bool _is_force;
  const bool _is_old_force;
  const bool _is_residual;
  const bool _is_parameter;
  const bool _is_other;
  const bool _is_solve_dependent;
};
 
template <typename T>
class Variable : public VariableBase
{
public:
  template <typename T2 = T, typename = typename std::enable_if_t<!std::is_same_v<Tensor, T2>>>
  Variable(const VariableName & name_in,
           const Model * owner,
           TensorType type = TensorTypeEnum<T2>::value)
    : VariableBase(name_in, owner),
      _type(type),
      _base_sizes(T::const_base_sizes)
  {
  }
 
  template <typename T2 = T, typename = typename std::enable_if_t<std::is_same_v<Tensor, T2>>>
  Variable(const VariableName & name_in,
           const Model * owner,
           TensorShapeRef base_shape,
           TensorType type = TensorType::kTensor)
    : VariableBase(name_in, owner),
      _type(type),
      _base_sizes(base_shape.vec())
  {
  }
 
  virtual void setup_views(const LabeledVector * value,
                           const LabeledMatrix * deriv = nullptr,
                           const LabeledTensor3D * secderiv = nullptr) override
  {
    VariableBase::setup_views(value, deriv, secderiv);
    if (value)
      _value = T(_raw_value.view(sizes()), batch_dim());
  }
 
  virtual void setup_views(const VariableBase * other) override
  {
    VariableBase::setup_views(other);
    _value = T(_raw_value.view(sizes()), batch_dim());
  }
 
  virtual void requires_grad_(bool req = true) override { _value.requires_grad_(req); }
 
  virtual TensorShapeRef base_sizes() const override { return _base_sizes; }
 
  virtual TensorShapeRef sizes() const override { return _sizes; }
 
  [[deprecated("Variable<T> must be assigned to references -- missing &")]] Variable(
      const Variable<T> &)
  {
  }
 
  [[deprecated("Variable<T> must be assigned to references -- missing &")]] void
  operator=(const Variable<T> &)
  {
  }
 
  void operator=(const Tensor & val)
  {
    _value.index_put_({torch::indexing::Slice()},
                      val.batch_expand(batch_sizes()).base_reshape(base_sizes()));
  }
 
  const T & value() const { return _value; }
 
  virtual const Tensor tensor() const override { return _value; }
 
  virtual TensorType type() const override { return _type; }
 
  T operator-() const { return -_value; }
 
  operator T() const { return _value; }
 
  virtual void cache(TensorShapeRef batch_shape) override
  {
    VariableBase::cache(batch_shape);
    _sizes = utils::add_shapes(batch_shape, _base_sizes);
  }
 
  template <typename T2 = T, typename = typename std::enable_if_t<!std::is_same_v<T2, Tensor>>>
  operator Tensor() const
  {
    return _value;
  }
 
protected:
  const TensorType _type;
 
  const TensorShape _base_sizes;
 
  TensorShape _sizes;
 
  T _value;
};
 
class Derivative
{
public:
  Derivative(Tensor & val)
    : _value(val)
  {
  }
 
  const Tensor & value() const { return _value; }
 
  Derivative & operator=(const Tensor & val);
 
private:
  Tensor & _value;
};
 
// Everything below is just for convenience: We just forward operations to the the variable values
// so that we can do
//
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//   var4 = (var1 - var2) * var3
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// instead of the (ugly?) expression below
//
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//   var4 = (var1.v - var2.v) * var3.v
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#define FWD_VARIABLE_BINARY_OP(op)                                                                 \
  template <typename T1,                                                                           \
            typename T2,                                                                           \
            typename = typename std::enable_if_t<std::is_base_of_v<VariableBase, T1> ||            \
                                                 std::is_base_of_v<VariableBase, T2>>>             \
  auto op(const T1 & a, const T2 & b)                                                              \
  {                                                                                                \
    if constexpr (std::is_base_of_v<VariableBase, T1> && std::is_base_of_v<VariableBase, T2>)      \
      return op(a.value(), b.value());                                                             \
                                                                                                   \
    if constexpr (std::is_base_of_v<VariableBase, T1> && !std::is_base_of_v<VariableBase, T2>)     \
      return op(a.value(), b);                                                                     \
                                                                                                   \
    if constexpr (!std::is_base_of_v<VariableBase, T1> && std::is_base_of_v<VariableBase, T2>)     \
      return op(a, b.value());                                                                     \
  }                                                                                                \
  static_assert(true)
FWD_VARIABLE_BINARY_OP(operator+);
FWD_VARIABLE_BINARY_OP(operator-);
FWD_VARIABLE_BINARY_OP(operator*);
FWD_VARIABLE_BINARY_OP(operator/);
}